| At present,the problem of energy shortage is increasingly serious,and the traditional fossil fuels will produce a lot of harmful gases in the process of power generation.As a new power supply and distribution system integrating renewable energy generation,energy storage and load,microgrid can reduce the use of fossil energy and improve environmental pollution.However,microgrid involves comprehensive utilization of light,wind,gas,electricity and user demand side.The randomness of these resources leads to more complex energy scheduling problems of microgrid compared with traditional power grid.Therefore,it is of high theoretical significance and application value to study how to optimize the scheduling of economy and power supply security of microgrid by using intelligent algorithm.Firstly,to solve the problem that the traditional microgrid scheduling model is difficult to combine economy and optimal configuration,a two-layer optimal scheduling model of microgrid is established.The upper layer model takes the daily fixed investment cost,the loss of load rate and the energy excess rate as the targets to allocate the capacity of the microgrid.The lower level model controls the economic benefits of microgrid by aiming at the lowest cycle operation and maintenance cost,pollutant emission cost and fuel cost.The superiority of the model is verified by improving the multi-objective particle swarm optimization algorithm and simulation based on the independent microgrid example.Secondly,in view of the large amount of computation and low accuracy of traditional multi-objective particle swarm optimization algorithm,external file maintenance is combined with global optimal location selection,and niche technology and non-dominated sorting strategy are introduced to improve the traditional multi-objective particle swarm optimization algorithm.The multi-objective particle swarm optimization algorithm before and after the improvement is tested by the test function,and the results show that the performance of the improved algorithm is better than the traditional multi-objective particle swarm optimization algorithm.Finally,taking the independent microgrid as the research object,the algorithm before and after the improvement is used in MATLAB to solve the established model.Through comparative analysis,it is concluded that the microgrid model obtained by the improved multi-objective particle swarm optimization algorithm has higher economy,environmental protection and power supply security.In addition,by comparing the dispatching scheme and dispatching cost with or without demand-side response and energy storage in the microgrid,the results show that under the condition of demand-side response and energy storage participating in the dispatching,the comprehensive cost of the microgrid is lower and the capacity of peaking and valley filling is stronger,which verifies the scientific nature of the model. |
